A robust dynamic mode decomposition methodology for an airfoil undergoing transonic shock buffet

Dynamic mode decomposition (DMD) is a data-driven technique widely used to analyze and model fluid problems including transonic buffet flows. Despite its strengths, DMD is known to suffer from sensitivities to the selected settings and the characteristics of the employed data. In this work, we closely examine the aforementioned sensitivities, identify possible pitfalls, and provide best practices to robustly perform DMD on a flow exhibiting transonic shock buffet. Specifically, we assess various DMD variants and test their sensitivity to the POD rank truncation, the sampling rate, and the time window. A critical enabler to our analysis is a new presentation of the DMD algorithm as a modular framework consisting of five distinct steps. The test results show a high sensitivity to rank truncation and a low sensitivity to the time window selection when a reasonable time period is used. The tests also highlight the existing dangers of aliasing, when the sampling rate is too low. Finally, a list of practical recommendations and guidelines on how to accurately and robustly perform DMD on a transonic buffet flow is provided.